Test Week: On the Rebound
If widespread, cheap, rapid Covid-19 testing is implemented, will people relax their own choices in managing contagion risk?
Welcome to Plugging the Gap (my email newsletter mainly about Covid-19 and its economics). My goal is for several posts a week explaining economic research and the economic approach to understanding the pandemic. (In case you don’t know me, I’m an economist and professor at the University of Toronto. I have written lots of books including most recently on Covid-19. You can follow me on twitter (@joshgans) or subscribe to this email newsletter here).
This week we are discussing testing in this newsletter. Yesterday’s post outlined how cheap, rapid tests could mitigate and, ultimately, conquer the Covid-19 pandemic. Today’s post looks at the full, potential effects of rolling out a widespread testing regime. While testing people and isolating them can reduce viral spread, the open question is what a program such as this would do to people’s other risk-mitigating behaviour, such as social distancing, mask-wearing and the like. Can this cause a rebound effect that creates more infections and what actions can we take to minimise that possibility?
Let me begin with a short extract from the book coming in November. These passages were the very last thing I added to the book.
Beware Rebounds: Excerpt from The Pandemic Information Gap
Testing is a straightforward way to solve the pandemic information gap. By knowing who is infected and taking them out of the population, you can reduce the rate at which the virus circulates. But economists are known as ‘dismal’ scientists for a reason. What if doing testing changes the human equation?
Casting doubt on policies that ‘normal’ people consider obviously sensible has a long tradition in economics. Back in the 1960s, safety advocates called for laws to make seat belts compulsory in all cars. This makes sense. If you wear a seatbelt you save lives. Enter, economist, Sam Peltzman. Peltzman noted that when you are wearing a seatbelt, you are, indeed, safer. But that also means that, as a driver, you don’t have to work hard to drive safely. So even if drivers and their passengers are safer, there may be more accidents. He showed this led to harm elsewhere – most notably pedestrians.
Could the same thing happen if people feel safer in pandemics due to testing? We do not really know yet. But as a matter of theory, it is certainly possible. Testing reduces the risk of encountering an infected person in your daily activities. Thus, if before testing, you were afraid of such encounters, the better testing is, the less afraid you are. This means that some people will be less willing to practice social distancing (and other good behaviors such as mask-wearing). Now if everyone was tested, this wouldn’t be an issue as that decrease in social distancing would be safe and, indeed, the whole point in overcoming the pandemic information gap. But it is unlikely everyone will be tested. Instead, with only a fraction of the population tested, then as people socially distance less, there will be more infections from that. Will the overall rate of infection rise? It depends on whether the testing removes infected people at a larger rate than reduced social distancing increases infections. The point is that it is not certain that a rebound effect, like the one observed in automobile safety, could occur.
There are ways to mitigate this possibility. One way would be to identify the groups of people that are most likely to reduce their social distancing and ramp up testing for them. Another would be to combine testing with continual mandatory social distancing to ensure that rebounds can’t take place. Either way, when you factor in the human equation, you have to be somewhat cautious when thinking testing will be an instant cure-all for an already significant pandemic.
A little more on the rebound theory
The idea of rebounds is the economist’s go-to ‘there may be bad unintended consequences’ theory. Peltzman often appears in the first chapter of Econ101 textbooks. It’s not why economics was called the dismal science but it is why people often think of economists as dismal.
Broadly speaking the theory is an ‘on the one hand’ testing and isolation reduces the epidemiological spread of the virus for a given level of social activity followed by an ‘on the other hand’ if people know those who they interact with have tested negative, they don’t fear those interactions. One effect pushes infections down while the other counteracts that. The problem is that if testing is not 100% perfect or ubiquitous (which it won’t be), you can’t be sure that the end result won’t be more infections.
With respect to testing, this theory was outlined in recent papers by Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, and Asuman Ozdaglar and by Cameron Taylor. They focussed on the behavioural aspects of testing while, in my own research, I put the two together. I already outlined the bare bones of that theory in a previous post but my often time co-author, Stephen King, does a nice job of explaining the rebound effect in the following video. He uses masks as an example but the analysis for testing is broadly the same.
And if you want to get really technical, he explains the details here.
There are other potential unintended consequences from testing. The first is that if you have a test and find out you are infected, then you know you are not at risk of being ‘more infected’ from interactions with others. If you are selfish (and this wouldn’t be economics if we didn’t assume the worst in people), having that information will cause you to take more risks and harm other people. This was discussed in a paper by my Toronto colleague Rahul Deb and his co-authors. A similar effect occurs if people fear going into quarantine. Another paper suggested that this might cause people not to be tested if that is the consequence. Fortunately, that doesn’t necessarily increase viral spread but it does reduce our ability to use testing to do that.
The point of all of this is that we can’t assume people when we roll out widespread testing will act in a compliant way to pull together. Instead, we must plan for the reverse lest we undermine all of our good intentions.
That we need to do this is often not appreciated by medical scientists who advocate testing. Michael Mina, who has recently been pushing more than most for cheap, frequent testing, has a discussion where he likens different testing options to a Nespresso machine (where you buy a machine and test people in the workplace) or instant coffee (which you can just make cheaply at home). He advocates the latter arguing for people to take the test and if positive, not go out of the house. But what we need to plan for is whether people will actually do that?
Consider this. Suppose you have an important flight. You take the test at home and it is positive. What then? Do you go to take the flight anyhow? If you are asked to self-report your test results that is an option. But if the flight is important or not refundable or something, your incentives are all screwed up at this point. And if you think that isn’t an issue remember this, we already ask people to self-report temperature checks etc. Do we think that all of those people are acting as they should?
The solution to this is obvious: an airline would have people take a test at the airport. That makes sense but we should also remember that when it comes to health tests and the like, especially if they are consequential as we intend them to be here, then this starts to encroach on privacy laws. This might happen for workplaces who want to use testing. I’m neither an epidemiologist nor a lawyer but I can spot icky problems when I see them.
In any case, a principle that self-reported tests are likely not to be what we want is a decent place to start. We will have to work out the legalities later.
Does this mean there is no room for the in-home test? Not at all. If you know the airport is going to test you when you get there, if you take a test at home you can make other plans. Knowing that whatever you do will be verified, makes it valuable to test for your own information.
The Bottom Line
Rebounds mean that the impact on testing on infection rates may not be as strong as we might hope. It happens because testing allows people to engage in more normal, social activity. We need to remember that that is the whole point. We want to get that activity back and we want it to be safer.
It is only if we want to use testing to wipe out the virus in a short period of time that it might be better to restrict activity as well. In that case, we need to make sure people behave and be prepared to take measures to ensure that happens.